Previous articles have discussed the PANCROMA image registration utilities designed specifically for subsetting and co-registering sets of Landsat band files for gap-filling and cloud masking. These utilities, although powerful have certain limitations. They always are combined with subsetting and a row and column rationalizing steps. They automatically select ground reference points using common UTM latitude and longitude coordinates. When rescaling, they always rescale the larger scale image down to the size of the smaller scale image.

Sometimes you may need a general image registration utility that merely aligns two images without cropping or subsetting either of them. You may wish to use ground control points rather than latitude and longitude, and you may wish to interpolate the smaller image to that of the larger scale. PANCROMA's preprocessing image registration utility can do this.

Image registration is the process of aligning two images of the same area of the earth such that they correspond to each other on an exact pixel-by-pixel basis. This can be though of as holding two image transparencies up to the light - if properly registered the land and water features will overlap exactly. It is rarely possible to produce a perfectly exact match. However, it is generally possible to produce very close matches for certain classes of images. One example is Landsat scenes. Different Landsat images taken of the same scene posses a high degree of commonality. However they can also differ in the following ways:

Corner coordinates generally will not match exactly

Row and column counts will usually be different

Obvious translational differences will exist with respect to the upper left corner of the image (which is commonly taken as the 0,0 row and column coordinate)

Scales may differ - some Landsat scenes have a resolution of 30m per pixel while earlier images have a slightly higher resolution of 28.5m/pixel

Sometimes it is necessary to adjust two similar images so that these and other differences are minimized and the two images align, for example in gap-filling, cloud masking and creating image mosaics.

Image registration is accomplished by conducting one or more image transformations to one of the images so that it matches the other. There are many types of transformations, for example linear, affine, approximations, piecewise methods, etc. They all work by building transformation functions using reference points (called control points) on both images that are known to describe the same point on the earth's surface. The transformation functions contain parameters or coefficients that are constructed using mathematical models describing the expected differences between the two images. PANCROMA uses a relatively simple linear transformation in its general registration function. Although simple in principle, its implementation in code can of course be less than simple. Linear transformations are generally appropriate for images that are acquired far from the earth's surface, and for data sets like Landsat are projected to a common datum and are oriented 'north is up'.

To use the utility, you must have two images that have at least some common area. (In order to avoid creating registered files that are very large and that contain a lot of collar space around the aligned images. Open the two files by selecting 'File' | 'Open' and opening two GeoTiff band files that you wish to register. The files should use the UTM projection and be oriented so that north is up. Now select 'PreProcess' | 'Register Images' | 'Linear Transformation Two Images'. A data entry box will be become visible. The next step is to select the ground control points (GCPs). GCPs are points on the base image that you can clearly identify on the image that you want to adjust so that it is registered with the base. There are a few rules of thumb regarding selection of such points. They should be clear, precise and preferably man-made. (Some natural features are clear and precise. However there is a possibility that they may shift position over time. Features such as river bends, edges of snow fields and the like may migrate over time and yield errors. Features such as crossroads and buildings are generally more reliable. The third characteristic is location. The points cannot be co-linear or the transformation coordinates cannot be computed. They should be spaced as far as possible apart and preferably close to the edges of the image.

The control points that I used for an example registration are shown to the right. The first image shows a distinct crossroads. (The corner of the white lot or a small building could have been used as well.) The second image shows some small islands that could serve as suitable control points. The third image shows the intersection of a road and a dry wash. Although using the wash could be dangerous, inspection of the two images showed the signatures to be exactly equal so I suspected that the location had not moved between the images.

You will need three control points for the registration. Select the first one by moving your cursor over it on the base image and clicking on it. Now locate the corresponding point on the second image and click on it. The second image will be adjusted during the registration process while the base image will remain unchanged (see note below). Return to the base image and click on the second point. Find its corresponding point on the adjust image and click on it. Repeat for the third point.

Each time you click on a point, its row and column coordinates will be displayed on the Image Registration form. If you make a mistake you can clear the text boxes or else just keep clicking, as the algorithm will just keep cycling until you stop. Once you have your three pairs of points recorded, select 'Enter' to start the computation.

PANCROMA will first compute the transformation coordinates based on the control point data that you have input. It will then apply the transformation to the adjust image. Since the transformation will not generally be a one-to-one mapping, narrow gaps will occur after the transformation. PANCROMA will fill these gaps using a Laplacian transformation interpolation algorithm.

Although the adjust image is generally mapped to the base image, there is a common case where the base image must also be adjusted. The transformation may compute negative adjust image row and column coordinates if the adjust image must be moved west and north. This cannot be so the necessary offset is applied to both the base and adjust images to prevent this from happening. The result is extra padding pixels added to the base image such that its row and column counts are increased by the offset amount. The UTM corner coordinates are then corrected to keep everything in order. If the base image adjustment goes the other way, the offset is not needed.

After the registration is computed, the graphics windows will display the base image, adjusted if necessary as explained above and the transformed adjust image. The images can be saved in GeoTiff format by selecting 'File' | 'Save' | 'Save Grayscale Image' | 'GeoTiff'. You will be asked to supply a base file name. When you do so and select 'Save', both images will be saved. They can be used for other purposes, or can be processed using future PANCROMA utilities, like image merge.